Triple

T8235676
Position Surface form Disambiguated ID Type / Status
Subject Garza E192398 entity
Predicate hasVariant P455 FINISHED
Object Garça
Garça is the Portuguese term for a heron, a long-legged wading bird commonly found near wetlands and waterways.
E726286 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Garça | Statement: [Garza, hasVariant, Garça]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Garça
Context triple: [Garza, hasVariant, Garça]
  • A. Guaratinguetá
    Guaratinguetá is a historic municipality in southeastern Brazil known for its colonial heritage and religious tourism, located in the state of São Paulo.
  • B. Mourão
    Mourão is a small municipality in Portugal’s Alentejo region, known for its historic castle and proximity to the Alqueva Reservoir.
  • C. Ribeirão Pires
    Ribeirão Pires is a municipality in the Greater São Paulo metropolitan region of Brazil, known for its green areas and role as a residential and service hub near the state capital.
  • D. Morrinhos
    Morrinhos is a municipality in the Brazilian state of Goiás, known for its agricultural economy and regional thermal springs.
  • E. Taquaritinga
    Taquaritinga is a municipality in the interior of Brazil’s São Paulo state, known for its agricultural production and regional commerce.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Garça
Triple: [Garza, hasVariant, Garça]
Generated description
Garça is the Portuguese term for a heron, a long-legged wading bird commonly found near wetlands and waterways.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Garça
Target entity description: Garça is the Portuguese term for a heron, a long-legged wading bird commonly found near wetlands and waterways.
  • A. Guaratinguetá
    Guaratinguetá is a historic municipality in southeastern Brazil known for its colonial heritage and religious tourism, located in the state of São Paulo.
  • B. Mourão
    Mourão is a small municipality in Portugal’s Alentejo region, known for its historic castle and proximity to the Alqueva Reservoir.
  • C. Ribeirão Pires
    Ribeirão Pires is a municipality in the Greater São Paulo metropolitan region of Brazil, known for its green areas and role as a residential and service hub near the state capital.
  • D. Morrinhos
    Morrinhos is a municipality in the Brazilian state of Goiás, known for its agricultural economy and regional thermal springs.
  • E. Taquaritinga
    Taquaritinga is a municipality in the interior of Brazil’s São Paulo state, known for its agricultural production and regional commerce.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca82dc8f148190a2c75a98501a7b91 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb782a5e18819096235679f5a644a8 completed March 31, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd94e168688190aa0a7149a4f8c4b0 completed April 1, 2026, 9:57 p.m.
NEDg Description generation batch_69cdab59ac188190ac017651b5a9a04a completed April 1, 2026, 11:33 p.m.
NED2 Entity disambiguation (via description) batch_69cdb2ae376c8190b3918ba6b269dba9 completed April 2, 2026, 12:05 a.m.
Created at: March 30, 2026, 5:46 p.m.